EP4111855A1 - Snp based panel for mediterranean wheat plant selection and breeding - Google Patents

Abstract

The present invention relates to a set of 38 SNP markers for genotyping 38 SNP sites in the wheat genome associated with specific agronomic traits of interest for wheat cropping in the Mediterranean area. Further provided is a method to detect favourable wheat trait genetic loci for marker assisted selection (MAS) to select parents for wheat breeding under Mediterranean climate. The invention also provides a kit comprising the set of 38 SNP markers.

Description

FIELD OF THE INVENTION
• The present invention relates to the field of biotechnology, in particular to a set of single nucleotide polymorphism (SNP) for marker assisted selection of wheat plants.
BACKGROUND OF THE INVENTION
• Wheat is the third most-important cereal crop in the world. To meet future market demands, some of the most important breeding objectives include increasing total yields and the rate at which wheat breeding programs adapt to new and changing environments, each time more frequent, mainly caused by climatic reasons. In crop breeding, the interest of predicting the performance of candidate cultivars in the field has increased due to recent advances in molecular breeding technologies. However, the complexity of the wheat genome presents some challenges for applying new technologies in molecular marker identification generating large numbers of molecular markers (SNPs) for use in genetic analyses such as genomics-assisted breeding in a range of plant species. Genotyping of crops allows breeders to conduct genomic selection (GS) on germplasm of interest using all available markers (phenotypic and genotypic) for a population as predictors of a breeding value. GS integrates marker data from a training population with phenotypic and pedigree data collected on the same population to generate a prediction model. The model outputs genomic estimated breeding values (GEBVs) for all genotyped individuals within a breeding population. GEBV is used as a predictor of how well a plant will perform as a parent for crossing and generation advance in a breeding pipeline, based on the similarity of its genomic profile to other plants in the training population that are known to have performed well in the target environment(s). The advantage of genomics-assisted breeding is that genotypic data obtained from a seed or seedling can be used to predict the phenotypic performance of mature individuals without the need for extensive phenotypic evaluation over years and environments. Genomic selection models have already proven to be advantageous but they are still quite laborious requiring the access to high throughput genotyping platforms and well trained and experienced personnel on bioinformatics and biostatistics to conduct prediction based on mathematical models. Therefore there is a need to develop methods allowing the use of shorter panels of molecular markers that can be used for germplasm screening in local breeding plant stations.
• Although bread and durum wheat are important crops cultivated worldwide, wheat cropping is strongly dependent on climatic conditions. According to recent data, despite the increasing wheat plantings in 2021 in the United States of America and Canada, adverse climatic conditions decreased yield prospects for the main winter wheat crop and consequently wheat production is expected to be below average. Although in European Union the expansion of winter wheat planting is expected to lead to higher production yields, wheat production in the Southern Mediterranean countries is mostly dependent on weather conditions and water availability, being especially fragile under very high spring temperatures and long periods of land drought.
• Grain yield (GY) improvement is one of the most challenging objectives in wheat breeding due to the complex genetic architecture and low heritability. Wheat production in the Southern European region is facing problems of long periods of groundwater decreasing, limiting irrigation frequency and causing the abandonment of wheat crop production by farmers. Although conventional breeding attempts to increase grain yield potential, advances are relatively slow as GY is a complex trait, strongly associated with spike number per unit area, kernel number per spike and thousand-kernel weight (TKW). However, some traits have higher heritabilities (h²) than GY, although also affecting it, such as grain shape, spike architecture, plant height (PH) or flag leaf related traits, impacting in processes like photosynthetic intensity, grain filling and dry matter translocation. The above mentioned traits are easier to select in small plots at the early stages of breeding programs.
• Most improvements in grain yield, including in the Alentejo region, were mainly related to the use of dwarfing genes and 1BL.1RS translocation lines to increase kernels per square meter, biomass and harvest index and reduced pH. Nowadays, after this renewed gene fixation, new strategies for variation must be envisaged. One of these strategies consists of the understanding of detailed genetic structure combined with marker-assisted selection (MAS). MAS is becoming a routine technique to overcome yield bottleneck of conventional breeding in the improvement of wheat yield potential. However, MAS application depends on the number of trait genes strongly associated with molecular markers.
• Although there are many reports on quantitative trait loci (QTL) mapping and genome-wide association study (GWAS) on wheat yield and related trait loci, only a few have been applied in selection of wheat in breeding programs for the Mediterranean area, those being mainly for durum wheat (see for example: Pascual, L., Ruiz, M., López-Fernández, M. et al. Genomic analysis of Spanish wheat landraces reveals their variability and potential for breeding. BMC Genomics 21, 122 (2020).; Soriano, J.M.; Sansaloni, C.; Ammar, K.; Royo, C. Labelling Selective Sweeps Used in Durum Wheat Breeding from a Diverse and Structured Panel of Landraces and Cultivars. .; Mérida-García R, Liu G, He S, Gonzalez-Dugo V, Dorado G, Gálvez S, et al. (2019) Genetic dissection of agronomic and quality traits based on association mapping and genomic selection approaches in durum wheat grown in Southern Spain. PLoS ONE 14(2): e0211718.; Mangini G, Gadaleta A, Colasuonno P, Marcotuli I, Signorile AM, Simeone R, et al. (2018) Genetic dissection of the relationships between grain yield components by genome-wide association mapping in a collection of tetraploid wheats. PLoS ONE 13(1): e0190162.).
• Several wheat SNP arrays for genetic studies of yield, quality, disease resistance and stress tolerance were developed for genotyping. See Jin H, Wen WE, Liu JD, Zhai SN, Zhang Y, Yan J, Liu ZY, Xia XC, He ZH. Genomewide QTL mapping for wheat processing quality parameters in a Gaocheng 8901/ Zhoumai 16 recombinant inbred line population. Front Plant Sci. 2016;7:1032.; Liu JD, He ZH, Rasheed A, Wen WE, Yan J, Zhang PZ, Wan YX, Zhang Y, Xie CJ, Xia XC. Genome-wide association mapping of black point reaction in common wheat (Triticum aestivum L.). BMC Plant Biol. 2017;17:220.; Sun CW, Zhang FY, Yan XF, Zhang XF, Dong ZD, Cui DQ, Chen F. Genomewide association study for 13 agronomic traits reveals distribution of superior alleles in bread wheat from the yellow and Huai Valley of China. Plant Biotechnol J. 2017;15:953-69.; Valluru R, Reynolds MP, Davies WJ, Sukumaran S. Phenotypic and genomewide association analysis of spike ethylene in diverse wheat genotypes under heat stress. New Phytol. 2017;214:271-83.
• Wheat 50K and 15K SNP arrays are available for selecting important traits in wheat breeding programs and include SNP markers derived from the 35K, 90 K and 660 K wheat SNP arrays. For all SNP arrays, protocols are standardized and the data generated between different laboratories is comparable. In theory, the position of the SNPs on the chip is unique in the chromosome or genome, thus largely avoiding the typing problems caused by the multi-copy gene SNP. These wheat SNP chips have been used for wheat population structure, genetic variation, selection evolution and genome-wide association analysis.
• SNP markers are now the main tool for genetic studies and breeding of crop species. Analysis of GWAS data based on linkage disequilibrium (LD) provides a much higher resolution capacity to reveal the genetic pathway of complex traits. GWAS uses directly all the available germplasm bypassing the need of developing mapping segregation populations and allowing only one phenotyping cycle for multiple traits. The genetic variance of traits in crop species may be caused by a single SNP, but is more often attributed to several SNPs within a haplotype block and therefore, SNP-GWAS is being commonly applied in genetic studies of crop species.
• In Mediterranean-climate regions, temperate cereals like wheat are usually exposed to a severe water deficit during the grain filling period. This water deficit leads to reductions in canopy photosynthesis and lower levels of assimilate transfer to the grain, leading to low kernel weights and GY. Analysis of candidate genes and genome-wide association studies (GWAS) have been performed in wheat to identify SNP markers controlling traits such as dehydration tolerance (Lorenz AJ, Hamblin MT, Jannink JL. Performance of single nucleotide polymorphisms versus haplotypes for genome-wide association analysis in barley. PLoS One. 2010;5:e14079.; Garg, B.; Lata, C.; Prasad, M. A study of the role of gene TaMYB2 and an associated SNP in dehydration tolerance in common wheat. Mol. Biol. Rep. 2012, 39, 10865-10871.), grain yield (Wang, S.-X.; Zhu, Y.-L.; Zhang, D.-X.; Shao, H.; Liu, P.; Hu, J.-B.; Zhang, H.; Zhang, H.-P.; Chang, C.; Lu, J.; et al. Genome-wide association study for grain yield and related traits in elite wheat varieties and advanced lines using SNP markers. PLoS ONE 2017, 12, e0188662.), leaf traits (Huang, S.; Sun, L.; Hu, X.; Wang, Y.; Zhang, Y.; Nevo, E.; Peng, J.; Sun, D. Associations of canopy leaf traits with SNP markers in durum wheat (Triticum turgidum L. durum (Desf.)). PLoS ONE 2018, 13, e0206226. (Huang, S.; Sun, L.; Hu, X.; Wang, Y.; Zhang, Y.; Nevo, E.; Peng, J.; Sun, D. Associations of canopy leaf traits with SNP markers in durum wheat (Triticum turgidum L. durum (Desf.)). PLoS ONE 2018, 13, e0206226.) and others (Guerra, F.P.; Yáñez, A.; Matus, I.; del Pozo, A. Genome-Wide Association of Stem Carbohydrate Accumulation and Remobilization during Grain Growth in Bread Wheat (Triticum aestivum L.) in Mediterranean Environments. .).
• Documents disclosing single nucleotide polymorphisms and methods to detect them in wheat and other crops are known in the art such as CN105256044A that discloses a wheat molecular barcode based on a set of 43 SNPs for identification and discrimination of wheat varieties or CN107794308A that reveals specific SNP for identifying the traits of wheat grains, aiming mostly Asian cultivated wheat.
• In view of the above, there is a need to identify stable markers to assist wheat breeding for the Mediterranean area. Moreover, there is a need for identification of a reasonable number of markers associated to important agronomic traits for climate resilience and grain production that can easily and immediately be tested in local breeding without a big investment in high throughput equipment.
SUMMARY OF THE INVENTION
• Surprisingly, the aforementioned problem was solved by the present invention.
• The present invention provides a set of 38 SNP markers for genotyping 38 SNP sites in the wheat genome associated with specific agronomic traits of interest for wheat cropping in the Mediterranean area, the 38 SNP markers being AX-94620918, AX-94417303, AX-95199577, AX-94632981, AX-95192948, AX-94788624, AX-94527824, AX-94727639, AX-94498228, AX-94690456, AX-94386458, AX-94434561, AX-95227398, AX-94943234, AX-94465615, AX-94464372, AX-95161376, AX-94786426, AX-94600322, AX-94845724, AX-95224829, AX-94740863, AX-95140911, AX-94500018, AX-94478188, AX-94750708, AX-94438290, AX-95126960, AX-94558126, AX-95120137, AX-95009987, AX-94976788, AX-94418123, AX-94619314, AX-94659431, AX-95224463, AX-94418429 and AX-94426996.
• In a preferred embodiment, the specific traits of interest are thousand-grain-weight, heading days, hectolitre mass, maturity days, plant height, protein content and grain yield in kg/ha.
• The present invention also provides a method to detect favourable wheat trait genetic loci for marker assisted selection (MAS) to select parents for wheat breeding under Mediterranean climate, the method comprising the steps of: a) detecting the set of 38 SNP genotypes aforementioned in the plant DNA to be tested; b) comparing the genotypes of all 38 SNP loci of the tested germplasm.
• The invention further provides a kit comprising a primer combination for wheat plant SNP genotyping of the above 38 markers associated with agronomic traits of interest for wheat breeding under the Mediterranean area and climate.
• The set of 38 SNP markers is used in combination with PCR based methods for detecting polymorphism.
• The set of 38 SNP markers SNP markers is used in combination with PCR based methods for genotyping SNP loci in the wheat genome.
• The set of 38 SNP markers is user for detecting favourable wheat trait genetic loci to assist genomic selection of wheat seedlings from wheat breeding programs under Mediterranean climate.
BRIEF DESCRIPTION OF THE DRAWINGS
• Figure 1 shows the wheat Single Nucleotide Polymorphism (SNP) screening process scheme.
• Figure 2 represents a Manhattan plot summarizing the genome-wide association study (GWAS) results for one of the traits [Yield (kg/ha)] using a mixed linear model (MLM). This graph shows the physical position (bp) of each tested SNP in wheat's (T aestivum) reference genome (per chromosome) on the X-axis and -log(10) P-values from the MLM on the Y-axis.
• Figure 3 shows selected trait associated marker analysis for a subsample of bread wheat (117 lines or varieties).
• Figure 4 shows probe sequences of each marker tested in Figure 3.
• Figure 5 shows the tree diagram discriminating all wheat tested.
DETAILED DESCRIPTION OF THE INVENTION
• The object of the present invention is to provide a set of 38 SNP for genotyping 38 SNP sites in the wheat genome associated with specific agronomic traits of interest for wheat cropping and breeding in the Mediterranean area, the 38 SNP sites being AX-94620918, AX-94417303, AX-95199577, AX-94632981, AX-95192948, AX-94788624, AX-94527824, AX-94727639, AX-94498228, AX-94690456, AX-94386458, AX-94434561, AX-95227398, AX-94943234, AX-94465615, AX-94464372, AX-95161376, AX-94786426, AX-94600322, AX-94845724, AX-95224829, AX-94740863, AX-95140911, AX-94500018, AX-94478188, AX-94750708, AX-94438290, AX-95126960, AX-94558126, AX-95120137, AX-95009987, AX-94976788, AX-94418123, AX-94619314, AX-94659431, AX-95224463, AX-94418429 and AX-94426996.
• The 38 SNP sites are as follows:

  Marker	Chr	Position in the Chr (cM)
  AX-94620918	1B	658714142
  AX-94417303	1B	662154416
  AX-95199577	1D	479052654
  AX-94632981	1B	660454560
  AX-95192948	UNKNOWN	2130
  AX-94788624	6D	356737499
  AX-94527824	1D	412082431
  AX-94727639	6B	158201834
  AX-94498228	6B	191527596
  AX-94690456	UNKNOWN	2473
  AX-94386458	1A	3392719
  AX-94434561	5D	398606941
  AX-95227398	5D	398782794
  AX-94943234	1D	28574855
  AX-94465615	1B	40878671
  AX-94464372	4A	709612601
  AX-95161376	1B	20164825
  AX-94786426	6B	146838012
  AX-94600322	1D	9799741
  AX-94845724	UNKNOWN	1106
  AX-95224829	5B	1579438
  AX-94740863	4A	725802640
  AX-95140911	2D	651606397
  AX-94500018	UNKNOWN	2359
  AX-94478188	UNKNOWN	1920
  AX-94750708	2D	117840331
  AX-94438290	1B	216098693
  AX-95126960	7A	11087391
  AX-94558126	1B	447164883
  AX-95120137	3D	175407295
  AX-95009987	3D	558724167
  AX-94976788	7A	645028871
  AX-94418123	3D	559185141
  AX-94619314	5A	502372312
  AX-94659431	UNKNOWN	1928
  AX-95224463	5D	400280006
  AX-94418429	5A	509656247
  AX-94426996	5A	25618238

• In one embodiment, it is an object of the invention to provide a set of 38 SNP for genotyping 38 SNP sites in the wheat genome associated with specific traits of interest for wheat cropping using SNP-GWAS on a panel of wheat varieties from a breeding program for the Mediterranean climate. Preferably, the selected traits are thousand-grain-weight (also called 1000KW.g (PMG)), heading days, hectolitre mass in kg/hL, maturity days, plant height in cm, protein content in DW and grain yield in kg/ha.
• It is also an object of the present invention to provide a method to detect favourable wheat trait genetic loci for marker assisted selection (MAS) to select parents for wheat breeding under Mediterranean climate, the method comprising the steps of:
1. a) detecting the 38 SNP genotypes in the plant DNA to be tested;
2. b) comparing the genotypes of all 38 SNP loci of the tested germplasm.
• In one embodiment, the set of 38 SNP in combination with PCR based methods detects polymorphism or genotyping SNP loci in the wheat genome. The PCR based methods are selected from, for example, RT-PCR, High Resolution Melting (HRM) and the like.
• In another embodiment, the set of 38 SNP detects favourable wheat trait genetic loci to assist genomic selection of wheat seedlings from wheat breeding programs under Mediterranean climate.
• It is an additional object of the present invention to provide a kit comprising a primer combination for wheat plant SNP genotyping of 38 markers associated with agronomic traits of interest for wheat breeding under the Mediterranean area and climate.
• Therefore, the aims of the present invention are summarized as follows:
1. 1) identifying stable wheat loci associated to specific agronomic traits using SNP-GWAS on a panel of wheat varieties.
2. 2) detecting favourable wheat trait genetic loci for marker assisted selection (MAS) to select parents for wheat breeding under Mediterranean climate.
3. 3) detecting favourable wheat trait genetic loci set of markers to assist genomic selection of wheat seedlings from wheat breeding programs under Mediterranean climate.
4. 4) producing a kit comprising a primer combination for wheat plant SNP genotyping of markers associated to agronomic traits important for wheat breeding under the Mediterranean area.
• Genotyping means the detection of a nucleotide base polymorphism in the wheat genome in a specific SNP site. Preferably, the nucleotide base polymorphism is associated with agronomic traits, e. g. grain yield (GY) or others favourable to wheat cropping in a panel of wheat varieties (Table 1) under Mediterranean climate (high temperature and drought resilience).
• Single Nucleotide Polymorphism associated to the traits of interest were merged in a subset panel for easy and fast genotyping of wheat plants and uses on activities of wheat breeding and marker assisted selection under Mediterranean climate.
• Surprisingly, the present invention shows that a small subset of 38 SNP sites is enough to improve the efficiency of selection of wheat germoplasm on wheat breeding under Mediterranean climate. This subset has proven that it is useful to identify and/or differentiate the varieties shown in Table 1.
EXAMPLES
• Hereinafter, the present invention is described in more detail and specifically with reference to the examples, which are not intended to be limitative.
• The experimental methods described in the examples are all conventional methods unless otherwise specified. The materials, reagents and the like used in the following examples are commercially available unless otherwise specified. In the quantitative experiments of the examples, three replicate experiments were set and the results were averaged.
Example 1. Discovery of specific SNPs and design of specific primer sets Screening of SNP loci
• The wheat used in this example consisted of 117 varieties of wheat as shown in Table 1 below. Wheat germoplasm, including local varieties and modern cultivars, were widely planted in wheat cultivation areas in Alentejo, Portugal, since 1940s. These materials carry important agronomic trait genes, drought tolerance genes, high quality, large grain, large ear and other favourable agronomic traits. Some materials have been used as backbone parents to produce new wheat varieties. The set of wheat from table 1 was used to screen SNPs. All the wheat lines or varieties are from "Instituto Nacional de Investigação Agrária e Veterinária, I. P. (INIAV)" - "Estação Nacional de Melhoramento de Plantas - ENMP" at Elvas, Portugal, and are agronomically cultivated and characterized under the Mediterranean climate, under drought and high spring/summer temperatures. Table 1. List of 117 wheat varieties/advanced lines

  ID Breed	Species	Wheat line or variety from INIAV germplasm breeding panel
  22	Ta	PAIVA
  26	Ta	RESTAURAÇÃO
  102	Ta	PIRANA
  127	Ta	BOLONHA
  660	Ta	ARDITO
  897	Ta	GENTIL ROSSO
  927	Ta	MOCHO DE ESPIGA QUADRADA
  940	Ta	TEMPORÃO DE CORUCHE
  1339	Ta	MOCHO DE ESPIGA BRANCA
  1357	Ta	RIBEIRO
  1998	Ta	TE 1518
  2004	Ta	TE 1414
  2049	Ta	AMAZONAS
  2065	Ta	CAIA
  2109	Ta	SUNCO/2*PASTOR
  2210	Ta	NABÃO
  2650	Ta	PYN"S"/BOW"S"
  3457	Ta	VPRT2 x VPRT3
  3484	Ta	EUFRATES
  3485	Ta	MONDEGO
  3486	Ta	JORDÃO
  3487	Ta	SEVER
  3511	Ta	CÔA
  3538	Ta	PASTOR//MUNIA/ALTAR
  3759	Ta	ATTILA/3/3*BCN//TOBA97
  3942	Ta	DEGEBE
  4028	Ta	(TJB368.251/BUC x TROCADERO)
  4112	Ta	ASP"S"/BLT"S"//HAHN"S"*2/PRL"S "
  4281	Ta	QG 78.5//2*INQALAB91*2/TUKURU
  4455	Ta	ALMANSOR
  4458	Ta	ROXO
  4527	Ta	CHAPIO/3/BORL95/2*EXCALIBUR//E XCALIBUR
  5022	Ta	NZT/BEZ1//ALD/4/NAD//TMP/CI!"$ =&/3/EMU
  5032	Ta	WAXWING*2/4/SNI/TRAP#1/3/KAUZ* 2/TRAP//KAUZ
  5391	Ta	INGENIO
  5403	Ta	ADÁGIO
  5428	Ta	KA/NAC//TRCH/3/VORB
  5446	Ta	BABAX/LR42/ /BABAX*2/4/SNI/TRAP 31/3/KAUZ*27TRAP/ /KAUZ75/WHEAR 7SOKOLL
  5464	Ta	ND643/2*WBLL1/4/CHIBIA/ /PRLI/C M6553173/SKAUZ/BAV92/5/BECARD
  5472	Ta	BAVIS//ATTILA*2/PBW65
  5505	Ta	KACHU*2//WHEAR/SOKOLL
  5512	Ta	GALERA
  5614	Ta	ENEBRO
  5615	Ta	AVELINO
  5616	Ta	MONTE CARLO
  5620	Ta	ANTEQUERA
  5953	Ta	(FLORIDA302 X TROCADERO) X (PRL/SARA/ /TSI/VEE#5...)
  5997	Ta	(CORDIAL X KI/PMFN/3//77C/CNO67... .) X TE0206
  6110	Ta	KATUNGA X (CENTAURO/VEJA)
  6380	Ta	(TAST/SPRW//ZAR/5/YUANDONG3/4/ PPBB-68/CHRC/3/PYN/ /TAM101/AMI...
  6425	Ta	ACCROC
  6461	Ta	MH12-32
  6592	Ta	MH12-24
  6684	Ta	KWS W204
  6704	Ta	KWS W227
  6719	Ta	SY10110
  7129	Ta	CHIBIA//PRLII/CM65531/3/5KAUZ/ BAV92/4/...
  7514	Ta	KAUZ"S"/SERI/3/TEVEE"S"//CROW/
  		VEE"S"
  8020	Ta	SOKOLL//PU894.15.1.12/WBLL1
  8173	Ta	VORB74/D67.2/PARANA 66.270//AE.SQUARROSA (3209/37CUNNIGHAM/5/D67.2..
  8173	Ta	VORB/4/D67.2/PARANA66.270//AE. SQUARROSA (320) /3/...
  8310	Ta	SUR.388-150
  8312	Ta	FILON
  8315	Ta	MAUPASSANT
  8325	Ta	(GOLIA X CEZANNE) X (IDEAL X TE8902)
  8326	Ta	(KENNEDY X ROXO)
  8349	Ta	AMUR/3/KINGBIRD#1/ /INQALAB91*2 /TUKURU/4/AMUR
  8352	Ta	BABAX/LR$"/ /BABAX*2/KUKURU/4/T X96V2427
  8353	Ta	BABAX/LR42/ /BABAX*2/3/VIVITS/4 /AGRI/NAC//ATTILA
  8364	Ta	NEOSHO/KS980508-1~1
  8364	Ta	NEOSHO/KS980508-1~1
  8371	Ta	DANPHE#1*2/SOLALA
  8374	Ta	GRK79//INQALAB91*2/TUKURU
  8403	Ta	PASTOR/MILAN/7/ZCL73/PGFN//CNO 67//SERI/5/UA.2837/...
  8411	Ta	PFAU/SERI.18//AMAD/3/WAXWING*2
  		/4/BECARD
  8422	Ta	TACUPETO F200176/CNDO/R143//ENTE/MEXI_2 /3/AEGILOPS SQUARROSA (TAUS)/4/WEAVER/... . .
  8428	Ta	SAUAL74/CROC_1/AE.SQUARROSA 82059//KAUZ/3/ATTILA/5/SAUAL/8 /TACUPETO F2001/6/....
  8438	Ta	KACHU#1/3/C80.1/3*BATAVIA//2*W BLL/4/KACHU/8/TACUPETO F2001/6/CNDO/R143//ENTE/...
  8485	Ta	(ARPIGE x ARCHAMP) x ARPIGE
  8661	Ta	PFAU7SERI.18/ /AMAD/3/WAXWING*2 /47TECU#1
  8670	Ta	BAV92/SERI
  8886	Ta	KACHU*2/BECARD
  8975	Ta	(GOLIA X CEZANNE) X (IDEAL X TE8902)
  8975	Ta	(GOLIA X CEZANNE) X (IDEAL X TE8902)
  9028	Ta	(GOELENT x BOLONHA) x ARDILA
  9028	Ta	(GOELENT X BOLONHA) X ARDILA
  9029	Ta	(GOELENT X BOLONHA) X ARDILA
  9048	Ta	(KENNEDY x ROXO)
  9167	Ta	(ORION X HEREWARD)
  9167	Ta	(ORION x HEREWARD)
  9170	Ta	(ORION X HEREWARD)
  9231	Ta	(FILIN/MILAN) x (TNMU/PASTOR)
  9377	Ta	KAUZ//ALTAR84/AOS/3/TNMU/MILAN /4/MILAN//PSN/BOW
  9396	Ta	NOGAL
  9578	Ta	KWSW22 0
  9579	Ta	INTENSIVNAYA/KUKUNA
  9581	Ta	WAXBI*2/COPIO
  9582	Ta	KWSW222
  9583	Ta	MACARENO
  9584	Ta	AFICIÒN
  9585	Ta	B2019_2
  9586	Ta	ELS12-61
  9588	Ta	ACORAZADO
  9589	Ta	TE 2002
  9590	Ta	MUTUS*2/TECUE#1/3/KINGBIRB#1/ / INQALAB91*2/TUKURU
  9591	Ta	BIZÃNCIO
  9592	Ta	ELYSIM
  9593	Ta	KWSW252
  9595	Ta	WHEAR/ /2*PRL/2*PASTOR/3/WAXBI/
  		4/COPIO
  9596	Ta	KWSW261
  9597	Ta	RW41269 (RGT Pembroke)
  9598	Ta	TE 2003
  9599	Ta	SPN/NAC//ATTILA/3/SHARK/F4105W 2.1
  9602	Ta	CNDO/R143//ENTE/MEXI_2/3/AEILO PS SQUARROSA...
  9604	Ta	CNDO/R148//ENTE/MEX_2/3/AE.SQU ARROSA...
  9607	Ta	SERI*3//RL6010/4*YR/3/PASTOR/4 /BAV92/5/...
  9613	Ta	(ATTILA/3/AGRI/NAC//MLT)XID#37 01/6/VPM/MOS83-11-4-8/ /PEW/7/... . .
  Ta = Triticum aestivum

1) DNA extraction
• All the materials shown in Table 1 were DNA extracted from seeds using a DNA extraction kit (AnalytycJena, Germany) according to the manufacturer's instructions.
2) Genotype detection
• Samples were quantified and when passing the quality test (1.8<OD260/280<2.0), normalized to a concentration of 23 ng/µL and distributed to 96 well PCR plates. SNP genotyping was performed as a service at Segalab (Portugal) using the Axiom^™ Wheat Breeder's Genotyping Array.
• Axiom summary files were converted to the desired fitPoly format using a custom python script. In detail, data was rearranged into columns "MarkerName", "SampleName", "X", "Y", "R" and "ratio" to accommodate the name of the SNP marker, the name of the sample, the A-allele intensity, the B-allele intensity, the sum of A and B intensities, and the ratio of intensity calculated as A/(B+A), respectively.
• The resulting converted data files were then imported to R [38] in order to assign genotypes to all samples using R package "fitPoly" [39]. For each marker, function "saveMarkerModels" was employed, which fitted multiple mixture models and selected the best fitting model based on the Bayesian Information Criterion (BIC), which takes into account the Log-Likelihood and the number of fitted parameters of the models.
• Genotypes were only accepted if they met several thresholds, namely p.threshold > 0.99 (default), call.threshold > 0.6 (default) and peak.threshold (default 0.85, was changed to 1.0 to allow for monomorphic markers). Genotype scores attributed by FitPoly (0 to 6) were diploidized for further use. In detail, numerical genotypes from FitPoly corresponding to the 6 possible allelic combinations (0 to 6) were converted to diploid equivalence, as follows: 0's were converted to homozygous genotype for one parent, codes 1-5 were converted to heterozygous genotype and 6's were converted to homozygous genotype for the other parent. The result of this diploidization was then converted into variant call format (VCF) in order to be used downstream for genotype-phenotype association studies.
• The SNP screening process based on 117 wheat varieties was according the scheme shown in Figure 1.
3) Genome-wide association study for SNP panel selection
• For identifying which SNP variants are associated with the specific traits in analysis, a standard Java-based software named TASSEL (Trait Analysis by aSSociation, Evolution and Linkage) was employed. TASSEL software for genome wide association analysis (GWAS) implements both general linear model (GLM) and mixed linear model (MLM) approaches for controlling population and family structure. In order to account for population structure, a Principal Component Analysis (PCA) was performed and the top five Principal Components (PCs) were used as covariates. Family structure was accounted for via a matrix of kinship coefficients (kinship matrix) that TASSEL calculates separately.
• The results presented in Figure 2 were obtained via the Q + K method, which uses a mixed linear model (MLM) function that can be described as follows: $$\mathrm{y}=\mathrm{X}\mathrm{\beta }+\mathrm{Z}\mathrm{\mu }+\mathrm{e}$$

  

  where "y" is the vector of observed phenotypes; "β" is an unknown vector containing fixed effects including genetic marker and population structure (Q); "µ" is an unknown vector of random additive genetic effects from multiple lines; "X" and "Z" are the known design matrices; and "e" is the unobserved vector of random residuals.
• The analysis of genotyping of wheat lines from Table 1 with the 38 SNP sites panel has provided the results shown in Figure 3, thus making evidence of genotype frequencies.
• The sequence of each of the 38 SNP markers selected in this invention is shown in Figure 4.
Example 2. 38 SNP panel in the differentiation of wheat varieties
• Genotype data for the 38 selected SNPs across the 117 bread wheat varieties was loaded into TASSEL software. The matrix of genetic distances between samples was calculated within the software, following a modified euclidean distance model, where distances are calculated as 1 minus the probability that alleles drawn at random from two individuals at the same locus are the same, or 1-IBS (Identical by state). This distance matrix was then used by the software to create a Neighbor-joining tree, as shown in Figure 5.
• The 38 SNP selected markers are able to discriminate/identify all the samples tested, and can therefore be used to identify a wheat variety/advanced line.

Claims (7)

1. A set of 38 SNP markers for genotyping 38 SNP sites in the wheat genome associated with specific agronomic traits of interest for wheat cropping in the Mediterranean area, the 38 SNP markers being AX-94620918, AX-94417303, AX-95199577, AX-94632981, AX-95192948, AX-94788624, AX-94527824, AX-94727639, AX-94498228, AX-94690456, AX-94386458, AX-94434561, AX-95227398, AX-94943234, AX-94465615, AX-94464372, AX-95161376, AX-94786426, AX-94600322, AX-94845724, AX-95224829, AX-94740863, AX-95140911, AX-94500018, AX-94478188, AX-94750708, AX-94438290, AX-95126960, AX-94558126, AX-95120137, AX-95009987, AX-94976788, AX-94418123, AX-94619314, AX-94659431, AX-95224463, AX-94418429 and AX-94426996.
2. The set of 38 SNP markers of claim 1 wherein the specific traits of interest are thousand-grain-weight, heading days, hectolitre mass, maturity days, plant height, protein content and grain yield in kg/ha.
3. A method to detect favourable wheat trait genetic loci for marker assisted selection (MAS) to select parents for wheat breeding under Mediterranean climate, the method comprising the steps of: a) detecting the set of 38 SNP genotypes of claim 1 in the plant DNA to be tested; b) comparing the genotypes of all 38 SNP loci of the tested germplasm.
4. Kit comprising a primer combination for wheat plant SNP genotyping of 38 markers according to claim 1 associated with agronomic traits of interest for wheat breeding under the Mediterranean area and climate.
5. Use of the set of 38 SNP markers of claim 1 in combination with PCR based methods for detecting polymorphism.
6. Use of the set of 38 SNP markers of claim 1 in combination with PCR based methods for genotyping SNP loci in the wheat genome.
7. Use of the set of 38 SNP markers of claim 1 for detecting favourable wheat trait genetic loci to assist genomic selection of wheat seedlings from wheat breeding programs under Mediterranean climate.

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